DOCSLIB.ORG

Blueprint Genetics Congenital Myasthenic Syndromes Panel

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Blueprint Genetics Congenital Myasthenic Syndromes Panel Congenital Myasthenic Syndromes Panel Test code: NE1701 Is a 21 gene panel that includes assessment of non-coding variants. Is ideal for patients with a clinical suspicion of a congenital myasthenic syndrome. About Congenital Myasthenic Syndromes Congenital myasthenic syndromes (CMS) are disorders of the neuromuscular junction resulting from abnormalities of presynaptic, synaptic, or post synaptic proteins. Abnormalities of proteins involved with neuromuscular transmission underlie CMS, limb girdle CMS, Pena-Shokeir syndrome, and multiple pterygium syndromes. These disorders may represent a phenotypic continuum of a single entity. Slow-channel CMS is caused by mutations in acetylcholine receptor subunits. Fatigable weakness affecting limb, ocular, facial, and bulbar muscles characterize CMS. Neonates present with feeding problems, choking, feeble cry, and facial, bulbar, and generalized skeletal muscle weakness. Patients presenting in later childhood typically have abnormal exercise-induced fatigue and difficulty running. Cardiac and smooth muscle are not involved. Cognitive skills, coordination, sensation, and tendon reflexes are normal. Most patients have symptoms prior to two years of age. Life threatening respiratory insufficiency may occur in affected neonates or older children. Availability 4 weeks Gene Set Description Genes in the Congenital Myasthenic Syndromes Panel and their clinical significance Gene Associated phenotypes Inheritance ClinVar HGMD AGRN Myasthenic syndrome, congenital AR 14 16 CHAT Myasthenic syndrome, congenital AR 24 73 CHRNA1 Myasthenic syndrome, congenital AD/AR 28 35 CHRNB1 Myasthenic syndrome AD/AR 11 11 CHRND Myasthenic syndrome AD/AR 18 26 CHRNE Myasthenic syndrome AD/AR 48 134 CHRNG Multiple pterygium syndrome, Escobar syndrome AR 17 34 COLQ Myasthenic syndrome, congenital AR 23 67 DOK7 Myasthenic syndrome, congenital AR 28 75 DPAGT1 Congenital disorder of glycosylation, Myasthenic syndrome, congenital AR 16 32 FLAD1 Lipid storage myopathy due to FLAD1 deficiency (LSMFLAD) AR 9 10 GFPT1 Myasthenic syndrome, congenital AR 13 42 LAMB2 Nephrotic syndrome, Pierson syndrome AR 20 122 https://blueprintgenetics.com/ MUSK Myasthenic syndrome, congenital AR 17 22 MYO9A Congenital myasthenic syndrome AR 6 PLEC Muscular dystrophy, limb-girdle, Epidermolysis bullosa AD/AR 36 103 PREPL Myasthenic syndrome, congenital 22 22 18 RAPSN Myasthenic syndrome, congenital AR 26 58 SCN4A Hyperkalemic periodic paralysis, Myotonia, potassium-aggravated, AD/AR 57 126 Paramyotonia congenita, Myasthenic syndrome, congenital, Normokalemic potassium-sensitive periodic paralysis STIM1 Stormorken syndrome, Immunodeficiency, Myopathy, tubular aggregate 1 AD/AR 13 24 SYT2 Myasthenic syndrome, congenital 7, presynaptic AD 3 3 *Some regions of the gene are duplicated in the genome. Read more. # The gene has suboptimal coverage (means <90% of the gene’s target nucleotides are covered at >20x with mapping quality score (MQ>20) reads), and/or the gene has exons listed under Test limitations section that are not included in the panel as they are not sufficiently covered with high quality sequence reads. The sensitivity to detect variants may be limited in genes marked with an asterisk (*) or number sign (#). Due to possible limitations these genes may not be available as single gene tests. Gene refers to the HGNC approved gene symbol; Inheritance refers to inheritance patterns such as autosomal dominant (AD), autosomal recessive (AR), mitochondrial (mi), X-linked (XL), X-linked dominant (XLD) and X-linked recessive (XLR); ClinVar refers to the number of variants in the gene classified as pathogenic or likely pathogenic in this database (ClinVar); HGMD refers to the number of variants with possible disease association in the gene listed in Human Gene Mutation Database (HGMD). The list of associated, gene specific phenotypes are generated from CGD or Mitomap databases. Non-coding disease causing variants covered by the panel Gene Genomic location HG19 HGVS RefSeq RS-number CHRNE Chr17:4804936 c.501-16G>A NM_000080.3 CHRNE Chr17:4806452 c.-94G>A NM_000080.3 CHRNE Chr17:4806453 c.-95G>A NM_000080.3 CHRNE Chr17:4806454 c.-96C>T NM_000080.3 rs748144899 RAPSN Chr11:47469717 c.193-15C>A NM_005055.4 RAPSN Chr11:47470715 c.-199C>G NM_005055.4 RAPSN Chr11:47470726 c.-210A>G NM_005055.4 rs786200905 Test Strengths The strengths of this test include: CAP accredited laboratory CLIA-certified personnel performing clinical testing in a CLIA-certified laboratory https://blueprintgenetics.com/ Powerful sequencing technologies, advanced target enrichment methods and precision bioinformatics pipelines ensure superior analytical performance Careful construction of clinically effective and scientifically justified gene panels Some of the panels include the whole mitochondrial genome (please see the Panel Content section) Our Nucleus online portal providing transparent and easy access to quality and performance data at the patient level Our publicly available analytic validation demonstrating complete details of test performance ~2,000 non-coding disease causing variants in our clinical grade NGS assay for panels (please see ‘Non-coding disease causing variants covered by this panel’ in the Panel Content section) Our rigorous variant classification scheme Our systematic clinical interpretation workflow using proprietary software enabling accurate and traceable processing of NGS data Our comprehensive clinical statements Test Limitations Genes with partial, or whole gene, segmental duplications in the human genome are marked with an asterisk (*) if they overlap with the UCSC pseudogene regions. The technology may have limited sensitivity to detect variants in genes marked with these symbols (please see the Panel content table above). This test does not d etect the following: Complex inversions Gene conversions Balanced translocations Some of the panels include the whole mitochondrial genome (please see the Panel Content section) Repeat expansion disorders unless specifically mentioned Non-coding variants deeper than ±20 base pairs from exon-intron boundary unless otherwise indicated (please see above Panel Content / non-coding variants covered by the panel). This test may not reliably detect the following: Low level mosaicism in nuclear genes (variant with a minor allele fraction of 14.6% is detected with 90% probability) Stretches of mononucleotide repeats Low level heteroplasmy in mtDNA (>90% are detected at 5% level) Indels larger than 50bp Single exon deletions or duplications Variants within pseudogene regions/duplicated segments Some disease causing variants present in mtDNA are not detectable from blood, thus post-mitotic tissue such as skeletal muscle may be required for establishing molecular diagnosis. The sensitivity of this test may be reduced if DNA is extracted by a laboratory other than Blueprint Genetics. For additional information, please refer to the Test performance section and see our Analytic Validation. Test Performance The genes on the panel have been carefully selected based on scientific literature, mutation databases and our experience. Our panels are sectioned from our high-quality, clinical grade NGS assay. Please see our sequencing and detection performance table for details regarding our ability to detect different types of alterations (Table). Assays have been validated for various sample types including EDTA-blood, isolated DNA (excluding from formalin fixed paraffin embedded tissue), saliva and dry blood spots (filter cards). These sample types were selected in order to maximize the likelihood for high-quality DNA yield. The diagnostic yield varies depending on the assay used, referring healthcare professional, hospital and country. Plus analysis increases the likelihood of finding a genetic diagnosis for your patient, as large deletions and duplications cannot be detected using sequence analysis alone. Blueprint Genetics’ Plus Analysis is a https://blueprintgenetics.com/ combination of both sequencing and deletion/duplication (copy number variant (CNV)) analysis. The performance metrics listed below are from an initial validation performed at our main laboratory in Finland. The performance metrics of our laboratory in Seattle, WA, are equivalent. Performance of Blueprint Genetics high-quality, clinical grade NGS sequencing assay for panels. Sensitivity % (TP/(TP+FN) Specificity % Single nucleotide variants 99.89% (99,153/99,266) >99.9999% Insertions, deletions and indels by sequence analysis 1-10 bps 99.2% (7,745/7,806) >99.9999% 11-50 bps 99.13% (2,524/2,546) >99.9999% Copy number variants (exon level dels/dups) 1 exon level deletion (heterozygous) 100% (20/20) NA 1 exon level deletion (homozygous) 100% (5/5) NA 1 exon level deletion (het or homo) 100% (25/25) NA 2-7 exon level deletion (het or homo) 100% (44/44) NA 1-9 exon level duplication (het or homo) 75% (6/8) NA Simulated CNV detection 5 exons level deletion/duplication 98.7% 100.00% Microdeletion/-duplication sdrs (large CNVs, n=37)) Size range (0.1-47 Mb) 100% (25/25) The performance presented above reached by Blueprint Genetics high-quality, clinical grade NGS sequencing assay with the following coverage metrics Mean sequencing depth 143X Nucleotides with >20x sequencing coverage (%) 99.86% Performance of Blueprint Genetics Mitochondrial Sequencing Assay. Sensitivity % Specificity % ANALYTIC VALIDATION (NA samples; n=4) Single nucleotide variants Heteroplasmic (45-100%) 100.0% (50/50) 100.0% Heteroplasmic (35-45%) 100.0% (87/87) 100.0% https://blueprintgenetics.com/
Load more

Recommended publications
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Genomic Landscape and Clonal Architecture of Mouse Oral Squamous Cell Carcinomas Dictate Tumour Ecology
    ARTICLE https://doi.org/10.1038/s41467-020-19401-9 OPEN Genomic landscape and clonal architecture of mouse oral squamous cell carcinomas dictate tumour ecology Inês Sequeira1,2, Mamunur Rashid3,5, Inês M. Tomás1,5, Marc J. Williams 4, Trevor A. Graham 4, ✉ David J. Adams 3, Alessandra Vigilante1 & Fiona M. Watt 1 1234567890():,; To establish whether 4-nitroquinoline N-oxide-induced carcinogenesis mirrors the hetero- geneity of human oral squamous cell carcinoma (OSCC), we have performed genomic analysis of mouse tongue lesions. The mutational signatures of human and mouse OSCC overlap extensively. Mutational burden is higher in moderate dysplasias and invasive SCCs than in hyperplasias and mild dysplasias, although mutations in p53, Notch1 and Fat1 occur in early lesions. Laminin-α3 mutations are associated with tumour invasiveness and Notch1 mutant tumours have an increased immune infiltrate. Computational modelling of clonal dynamics indicates that high genetic heterogeneity may be a feature of those mild dysplasias that are likely to progress to more aggressive tumours. These studies provide a foundation for exploring OSCC evolution, heterogeneity and progression. 1 Centre for Stem Cells & Regenerative Medicine, King’s College London, Guy’s Hospital, Great Maze Pond, London SE1 9RT, UK. 2 Institute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London E1 2AT, UK. 3 Experimental Cancer Genetics, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK. 4 Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK. 5These authors contributed equally: Mamunur Rashid and Inês M.
    [Show full text]
  • Congenital Disorders of Glycosylation from a Neurological Perspective
    brain sciences Review Congenital Disorders of Glycosylation from a Neurological Perspective Justyna Paprocka 1,* , Aleksandra Jezela-Stanek 2 , Anna Tylki-Szyma´nska 3 and Stephanie Grunewald 4 1 Department of Pediatric Neurology, Faculty of Medical Science in Katowice, Medical University of Silesia, 40-752 Katowice, Poland 2 Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland; [email protected] 3 Department of Pediatrics, Nutrition and Metabolic Diseases, The Children’s Memorial Health Institute, W 04-730 Warsaw, Poland; [email protected] 4 NIHR Biomedical Research Center (BRC), Metabolic Unit, Great Ormond Street Hospital and Institute of Child Health, University College London, London SE1 9RT, UK; [email protected] * Correspondence: [email protected]; Tel.: +48-606-415-888 Abstract: Most plasma proteins, cell membrane proteins and other proteins are glycoproteins with sugar chains attached to the polypeptide-glycans. Glycosylation is the main element of the post- translational transformation of most human proteins. Since glycosylation processes are necessary for many different biological processes, patients present a diverse spectrum of phenotypes and severity of symptoms. The most frequently observed neurological symptoms in congenital disorders of glycosylation (CDG) are: epilepsy, intellectual disability, myopathies, neuropathies and stroke-like episodes. Epilepsy is seen in many CDG subtypes and particularly present in the case of mutations
    [Show full text]
  • The First Case of Congenital Myasthenic Syndrome Caused by A
    G C A T T A C G G C A T genes Case Report The First Case of Congenital Myasthenic Syndrome Caused by a Large Homozygous Deletion in the C-Terminal Region of COLQ (Collagen Like Tail Subunit of Asymmetric Acetylcholinesterase) Protein Nicola Laforgia 1 , Lucrezia De Cosmo 1, Orazio Palumbo 2 , Carlotta Ranieri 3, Michela Sesta 4, Donatella Capodiferro 1, Antonino Pantaleo 3 , Pierluigi Iapicca 5 , Patrizia Lastella 6, Manuela Capozza 1 , Federico Schettini 1, Nenad Bukvic 7 , Rosanna Bagnulo 3 and Nicoletta Resta 3,7,* 1 Section of Neonatology and Neonatal Intensive Care Unit, Department of Biomedical Science and Human Oncology (DIMO), University of Bari “Aldo Moro”, 70124 Bari, Italy; [email protected] (N.L.); [email protected] (L.D.C.); [email protected] (D.C.); [email protected] (M.C.); [email protected] (F.S.) 2 Division of Medical Genetics, Fondazione IRCCS Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo, Italy; [email protected] 3 Division of Medical Genetics, Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari “Aldo Moro”, 70124 Bari, Italy; [email protected] (C.R.); [email protected] (A.P.); [email protected] (R.B.) 4 Neurology Unit, University Hospital Consortium Corporation Polyclinic of Bari, 70124 Bari, Italy; [email protected] 5 SOPHiA GENETICS SA HQ, 1025 Saint-Sulpice, Switzerland; [email protected] 6 Rare Diseases Centre—Internal Medicine Unit “C. Frugoni”, Polyclinic of Bari, 70124 Bari, Italy; [email protected] 7 Medical Genetics Section, University Hospital Consortium Corporation Polyclinic of Bari, 70124 Bari, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-0805593619 Received: 17 November 2020; Accepted: 15 December 2020; Published: 18 December 2020 Abstract: Congenital myasthenic syndromes (CMSs) are caused by mutations in genes that encode proteins involved in the organization, maintenance, function, or modification of the neuromuscular junction.
    [Show full text]
  • Limb Girdle Myasthenia with Digenic RAPSN and a Novel Disease Gene AK9 Mutations
    European Journal of Human Genetics (2017) 25, 192–199 & 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved 1018-4813/17 www.nature.com/ejhg ARTICLE Limb girdle myasthenia with digenic RAPSN and a novel disease gene AK9 mutations Ching-Wan Lam*,1,3, Ka-Sing Wong2,3, Ho-Wan Leung2 and Chun-Yiu Law1 Though dysfunction of neuromuscular junction (NMJ) is associated with congenital myasthenic syndrome (CMS), the proteins involved in neuromuscular transmission have not been completely identified. In this study, we aimed to identify a novel CMS gene in a consanguineous family with limb-girdle type CMS. Homozygosity mapping of the novel CMS gene was performed using high-density single-nucleotide polymorphism microarrays. The variants in CMS gene were identified by whole-exome sequencing (WES) and Sanger sequencing. A 20 MB-region of homozygosity (ROH) was mapped on chromosome 6q15–21. This was the only ROH that present in all clinically affected siblings and absent in all clinically unaffected siblings. WES showed a novel variant of AK9 gene located in this ROH. This variant was a start-gain mutation and introduced a cryptic 5′-UTR signal in intron 5 of the AK9 gene. The normal splicing signal would be interfered by the cryptic translation signal leading to defective splicing. Another 25 MB-ROH was found on chromosome 11p13–q12 in all siblings. WES showed a homozygous RAPSN pathogenic variant in this ROH. Since RAPSN-associated limb-girdle type CMS was only manifested in AK9 homozygous variant carriers, the disease phenotype was of digenic inheritance, and was determined by the novel disease modifier AK9 which provides NTPs for N-glycosylation.
    [Show full text]
  • DPAGT1 Antibody (Pab)
    21.10.2014DPAGT1 antibody (pAb) Rabbit Anti-Human/Mouse DPAGT1 (DGPT, GPT, ALG7, G1PT, UAGT, UGAT, CDG1J, CDG -Ij) Instruction Manual Catalog Number PK-AB718-6485 Synonyms DPAGT1 Antibody: DPAGT, DGPT, GPT, ALG7, G1PT, UAGT, UGAT, CDG1J, CDG-Ij, UDP-N- acetylglucosamine-dolichyl-phosphate N-acetylglucosaminephosphotransferase Description The UDP-N-acetylglucosamine-dolichyl-phosphate N-acetyl-glucosaminephosphotransferase (DPAGT1) is an enzyme that catalyzes the first step in the dolichol-linked oligosaccharide pathway for glycoprotein biosynthesis. Mutations in this integral endoplasmic reticulum (ER) membrane protein enzyme belongs to the glycosyltransferase family 4 results in the congenital disorder of glycosylation type Ij with symptoms such as severe hypotonia, medically intractable seizures, mental retardation, microcephaly, and exotropia. Recent experiments have shown that DPAGT1 is a target of the Wnt/beta-catenin signaling pathway, with Wnt3a inducing higher DPAGT1 mRNA expression. Quantity 100 µg Source / Host Rabbit Immunogen DPAGT1 antibody was raised against a 17 amino acid synthetic peptide near the amino terminus of human DPAGT1. Purification Method Affinity chromatography purified via peptide column. Clone / IgG Subtype Polyclonal antibody Species Reactivity Human, Mouse Specificity At least four isoforms of DPAGT1 are known to exist; this antibody will recognize the two longest isoforms. DPAGT1 antibody is predicted to not cross-react with UHRF1BP1. Formulation Antibody is supplied in PBS containing 0.02% sodium azide. Reconstitution During shipment, small volumes of antibody will occasionally become entrapped in the seal of the product vial. For products with volumes of 200 μl or less, we recommend gently tapping the vial on a hard surface or briefly centrifuging the vial in a tabletop centrifuge to dislodge any liquid in the container’s cap.
    [Show full text]
  • Targeted Polymerase Chain Reaction-Based Enrichment and Next Generation Sequencing for Diagnostic Testing of Congenital Disorders of Glycosylation Melanie A
    ARTICLE Targeted polymerase chain reaction-based enrichment and next generation sequencing for diagnostic testing of congenital disorders of glycosylation Melanie A. Jones, PhD1, Shruti Bhide, MS1, Ephrem Chin, MB(ASCP), QLC1, Bobby G. Ng, BS2, Devin Rhodenizer, BS1, Victor W. Zhang, MD, PhD1, Jessica J. Sun, MS1, Alice Tanner, PhD, MS1, Hudson H. Freeze, PhD2, and Madhuri R. Hegde, PhD, FACMG1 2 Purpose: Congenital disorders of glycosylation are a heterogeneous stability and in the immune response ; hence, the proper devel- group of disorders caused by deficient glycosylation, primarily affecting opment and functioning of many organ systems depend on the N-linked pathway. It is estimated that more than 40% of congenital normal N-glycosylation. Deficient N-glycosylation results in 3 disorders of glycosylation patients lack a confirmatory molecular multiple organ dysfunction that can be life threatening. Con- diagnosis. The purpose of this study was to improve molecular genital disorders of glycosylation (CDG) are a group of more diagnosis for congenital disorders of glycosylation by developing than 30 autosomal recessive disorders caused by deficient gly- 4 and validating a next generation sequencing panel for comprehensive cosylation, primarily affecting the N-linked pathway. Symp- mutation detection in 24 genes known to cause congenital disorders toms of CDG can include severe developmental delay, ataxia, of glycosylation. Methods: Next generation sequencing validation seizures, liver fibrosis, retinopathy, cardiac dysfunction, and 3,5 was performed on 12 positive control congenital disorders of gly- coagulopathies. CDG occurs worldwide, with an estimated 6 cosylation patients. These samples were blinded as to the disease- prevalence as high as 1 in 20,000.
    [Show full text]
  • Impacts of Massively Parallel Sequencing for Genetic Diagnosis of Neuromuscular Disorders
    Acta Neuropathol (2013) 125:173–185 DOI 10.1007/s00401-012-1072-7 REVIEW Impacts of massively parallel sequencing for genetic diagnosis of neuromuscular disorders Nasim Vasli • Jocelyn Laporte Received: 8 October 2012 / Revised: 27 November 2012 / Accepted: 28 November 2012 / Published online: 7 December 2012 Ó Springer-Verlag Berlin Heidelberg 2012 Abstract Neuromuscular disorders (NMD) such as neu- We remind the challenges and benefit of obtaining an ropathy or myopathy are rare and often severe inherited accurate genetic diagnosis, introduce the massively parallel disorders, affecting muscle and/or nerves with neonatal, sequencing technology and its novel applications in diag- childhood or adulthood onset, with considerable burden for nosis of patients, prenatal diagnosis and carrier detection, the patients, their families and public health systems. and discuss the limitations and necessary improvements. Genetic and clinical heterogeneity, unspecific clinical fea- Massively parallel sequencing synergizes with clinical and tures, unidentified genes and the implication of large and/or pathological investigations into an integrated diagnosis several genes requiring complementary methods are the approach. Clinicians and pathologists are crucial in patient main drawbacks in routine molecular diagnosis, leading to selection and interpretation of data, and persons trained in increased turnaround time and delay in the molecular data management and analysis need to be integrated to the validation of the diagnosis. The application of massively diagnosis pipeline. Massively parallel sequencing for parallel sequencing, also called next generation sequenc- mutation identification is expected to greatly improve ing, as a routine diagnostic strategy could lead to a rapid diagnosis, genetic counseling and patient management. screening and fast identification of mutations in rare genetic disorders like NMD.
    [Show full text]
  • Sphingomyelin Suppresses Hedgehog Signaling by Restricting Cholesterol Accessibility at the Ciliary Membrane
    bioRxiv preprint doi: https://doi.org/10.1101/699819; this version posted July 16, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Sphingomyelin suppresses Hedgehog signaling by restricting cholesterol accessibility at the ciliary membrane 1# 1# 1 1 1 Maia Kinnebrew ,​ Ellen J. Iverson ,​ Bhaven B. Patel ,​ Ganesh V. Pusapati ,​ Jennifer H. Kong ,​ Kristen A. 3 ​ 1,5 ​ 4 ​ 2 ​ 3* ​ Johnson ,​ Giovanni Luchetti ,​ Douglas F. Covey ,​ Christian Siebold ,​ Arun Radhakrishnan ​ and Rajat ​ ​ ​ ​ ​ Rohatgi1* ​ 1 Departments​ of Biochemistry and Medicine, Stanford University School of Medicine, Stanford, California, United States of America 2 Division​ of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK 3 Department​ of Molecular Genetics, University of Texas Southwestern Medical Center, Dallas, TX 75390 4 Department​ of Developmental Biology and Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, Missouri, United States of America 5 Current​ address: Department of Physiological Chemistry, Genentech, South San Francisco, CA # MK​ and EJI contributed equally to this study. * Correspondence​ to [email protected] or [email protected] bioRxiv preprint doi: https://doi.org/10.1101/699819; this version posted July 16, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
    [Show full text]
  • A Genomic Approach to Delineating the Occurrence of Scoliosis in Arthrogryposis Multiplex Congenita
    G C A T T A C G G C A T genes Article A Genomic Approach to Delineating the Occurrence of Scoliosis in Arthrogryposis Multiplex Congenita Xenia Latypova 1, Stefan Giovanni Creadore 2, Noémi Dahan-Oliel 3,4, Anxhela Gjyshi Gustafson 2, Steven Wei-Hung Hwang 5, Tanya Bedard 6, Kamran Shazand 2, Harold J. P. van Bosse 5 , Philip F. Giampietro 7,* and Klaus Dieterich 8,* 1 Grenoble Institut Neurosciences, Université Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, 38000 Grenoble, France; [email protected] 2 Shriners Hospitals for Children Headquarters, Tampa, FL 33607, USA; [email protected] (S.G.C.); [email protected] (A.G.G.); [email protected] (K.S.) 3 Shriners Hospitals for Children, Montreal, QC H4A 0A9, Canada; [email protected] 4 School of Physical & Occupational Therapy, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC H3G 2M1, Canada 5 Shriners Hospitals for Children, Philadelphia, PA 19140, USA; [email protected] (S.W.-H.H.); [email protected] (H.J.P.v.B.) 6 Alberta Congenital Anomalies Surveillance System, Alberta Health Services, Edmonton, AB T5J 3E4, Canada; [email protected] 7 Department of Pediatrics, University of Illinois-Chicago, Chicago, IL 60607, USA 8 Institut of Advanced Biosciences, Université Grenoble Alpes, Inserm, U1209, CHU Grenoble Alpes, 38000 Grenoble, France * Correspondence: [email protected] (P.F.G.); [email protected] (K.D.) Citation: Latypova, X.; Creadore, S.G.; Dahan-Oliel, N.; Gustafson, Abstract: Arthrogryposis multiplex congenita (AMC) describes a group of conditions characterized A.G.; Wei-Hung Hwang, S.; Bedard, by the presence of non-progressive congenital contractures in multiple body areas.
    [Show full text]
  • Breadth-First Search Based Approach to Enumerating Chemical Compounds Containing Outerplanar Fused Benzene Ring Substructures
    Breadth-first Search Based Approach to Enumerating Chemical Compounds Containing Outerplanar Fused Benzene Ring Substructures Jina Jindalertudomdee Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan Structure enumeration is a problem of generating all non-redundant chemical compounds based on a given constraint, such as a chemical formula. It is important in chemoinformatics since it appears as a subproblem of several critical problems, such as drug discovery and structure elucidation. Until now, various algorithms have been proposed to solve the structure-enumeration problem. With the goal of enumerating all possible structures, some tools require impractical computation time for a moderate number of atoms in the input chemical formula. Therefore, alternative tools that can be executed in a reasonable period of time, but have the restriction of the structure of enumerated compounds, were developed. For example, a combination of BfsSimEnum and BfsMulEnum1 can enumerate acyclic compounds efficiently using a tree structure to represent a chemical compound, where nodes and edges are labeled by atom types and bond multiplicities, respectively. This work presents a novel algorithm BfsFusedBenzeneEnum, the extension of BfsSimEnum and BfsMulEnum, for the enumeration of chemical compounds containing no cyclic substructures except for outerplanar fused benzene ring substructures. In BfsFusedBenzeneEnum, a tree structure is used to represent a chemical compound with outerplanar fused benzene ring substructures by defining a special atom type, called b, and a special kind of bond, called a merge bond, to represent a benzene ring and a fused bond between two benzene rings, respectively. A node labeled with an atom type b has an additional attribute called a carbon position list, to keep information about which carbon atoms in the corresponding benzene ring bond with which adjacent nodes.
    [Show full text]
  • High Throughput Genetic Analysis of Congenital Myasthenic Syndromes Using Resequencing Microarrays Lisa Denning1, Jennifer A
    High Throughput Genetic Analysis of Congenital Myasthenic Syndromes Using Resequencing Microarrays Lisa Denning1, Jennifer A. Anderson1, Ryan Davis2, Jeffrey P. Gregg2, Jennifer Kuzdenyi1, Ricardo A. Maselli1* 1 Department of Neurology, University of California at Davis, Davis, California, United States of America, 2 Department of Pathology, Medical Investigation of Neurodevelopmental Disorders Institute, University of California at Davis, Davis, California, United States of America Background. The use of resequencing microarrays for screening multiple, candidate disease loci is a promising alternative to conventional capillary sequencing. We describe the performance of a custom resequencing microarray for mutational analysis of Congenital Myasthenic Syndromes (CMSs), a group of disorders in which the normal process of neuromuscular transmission is impaired. Methodology/Principal Findings. Our microarray was designed to assay the exons and flanking intronic regions of 8 genes linked to CMSs. A total of 31 microarrays were hybridized with genomic DNA from either individuals with known CMS mutations or from healthy controls. We estimated an overall microarray call rate of 93.61%, and we found the percentage agreement between the microarray and capillary sequencing techniques to be 99.95%. In addition, our microarray exhibited 100% specificity and 99.99% reproducibility. Finally, the microarray detected 22 out of the 23 known missense mutations, but it failed to detect all 7 known insertion and deletion (indels) mutations, indicating an overall sensitivity of 73.33% and a sensitivity with respect to missense mutations of 95.65%. Conclusions/Significance. Overall, our microarray prototype exhibited strong performance and proved highly efficient for screening genes associated with CMSs. Until indels can be efficiently assayed with this technology, however, we recommend using resequencing microarrays for screening CMS mutations after common indels have been first assayed by capillary sequencing.
    [Show full text]